The purpose of this project is to conduct research in statistical methods and computer techniques with particular emphasis on those appropriate for analyzing data from clinical and diagnostic trials and epidemiological studies of cancer. Many of the problems studied under this project arise from the consultative activities of the Section. During the past year the use of factorial designs for clinical trials of agents which might present the development of cancer has been studied, with particular attention paid to nonlinear end points and the effect of plausible interactions on statistical power. Another major project involved a systematic analysis of data on stage at diagnosis and survival for patients with breast or colon cancer in all SEER counties in an effort to determine whether some areas had unusually poor survival or high state at diagnosis. Another important area of methodologic research was the analysis of maps of cancer mortality by SEA for the entire country. Using lung cancer in white males as an example, regression methods were used to relate geographic, economic, and demographic data to the observed mortality patterns, paying special attention to the problem of spatial autocorrelation. Other methodologic problems studied included the assessment of apparent treatment-covariate interactions arising in the analysis of data from clinical trials, sample size calculations for case-control studies with quantitative exposures, the effect on the size of tests for trend of optimal grouping of adjacent categories, and the use of case-control data for designing intervention studies for high risk groups.